1,720,985 research outputs found
Parking as a Challenge for Urban Mobility: Introduction
Full text linkThis part of the book collects smart city approaches to support parking, mostly focusing on the parking
pressure in inner-urban areas. The presented recipes for parking information and management
rely on a smart – sensor-infused, connected, digitally enhanced – urban parking infrastructure that
incorporates and utilizes the smart geospatial technologies presented in the first part. It also complements
the approaches presented at the end of the first part, which focused on avoiding and shifting
private motorized trips in cities, and thus alleviated parking pressure. The approaches presented
also weigh also their options when confronted with traffic on roads with less infrastructure and less
discipline
Geospatial Technologies for Urban Mobility: Introduction
Full text linkThis chapter gives a broad introduction to the topics in the first part of this book. This first part
considers a range of geospatial technologies for smart cities and urban mobility, and demonstrates
their potential to shape the future of urban mobility. In this way, the first part prepares the ground,
or the framework, for the second part that focuses on technologies for smart parking and specifically
on smart parking challenges in the context of cities where private motorization is not yet saturated.
Readers who are already familiar with geospatial technologies and are only interested in the parking
challenges, can jump ahead to the second part after this introduction
Mapping Parking Spaces Using Crowd-Sourced Trajectories
Full text linkMapping urban parking spaces helps drivers to reduce their search and cruising for parking, thus
reducing traffic, reducing emissions, and reducing total travel times. Mapped urban parking spaces
can also be monitored for real-time occupancy information. But while many cities in Asia, Africa,
and Latin America are experiencing a strong increase of private car use on the roads, they typically
lack such reliable information regarding on-street parking spaces. Hence, in this chapter we explore
globally applicable mapping methods for on-street parking locations, as a first step towards smart
parking (for an alternative approach see Chapter 11)
Tracking Urban Mobility
Full text linkWithin the coordinate reference systems discussed in the previous chapter, location can be described.
Location data is increasingly becoming available from sensors integrated in urban mobility:
sensors that are attached to travelers or vehicles, or even to fix locations registering travelers or vehicles
passing by. This chapter will introduce some tracking technologies and their properties, and
then define the notion of a trajectory, with its critical properties of spatial and temporal granularity
(precision and sampling rate), and accuracy (linked to map matching). In addition, the chapter introduces
the two complementary frames of references for tracking urban mobility, the Lagrangian and
the Eulerian, and how to convert between them
Smart parking in fast-growing cities
Full text link"Parking in cities is a challenge everywhere, but to a greater extent for the cities in low- and middle-income countries: Cities that are experiencing rapid urbanization and increasing motorization, where free on-street parking meets haphazard parking behaviour, and where investment capacity for parking infrastructure is limited.
This book is a resource book for those managing the urban parking challenges especially in low- and middle-income countries. This open-access book should immediately help city authorities, engineering firms, and academia world-wide to develop data-driven solutions – solutions of a smart city – for their specific context. This perspective is reflected in the approach of the book. The first part lays out the context of geospatial technologies for urban mobility in smart cities. The second focuses on parking information and management using these technologies, with an emphasis on low and middle-income countries.
The book has grown out of a project funded by the Indian Government, Advanced Parking Information and Management for Indian Traffic, a collaboration between IIT Kanpur and the University of Melbourne.
Reducing Parking Pressure by Sharing Resources
Full text linkThis chapter describes a scenario where ridesharing is introduced in urban parking to relieve the
pressure of finding a parking site in the city center. A significant amount of time is wasted in cruising
for a parking lot according to both life experience and research findings. Although a few policies
and strategies have been tested, the middle ground between individual flexibility and reduced travel
demand is not yet well accommodated. Therefore, I report of a joint model of ridesharing and parking:
people drive from their front doors to a satellite parking site to share rides, and travel to a similar
destination in the city center so that parking demand is reduced
Urban Mobility and Parking Demand
Full text linkParking demand, both current and future, depends on two aspects: the long-term impact of urbanization
and urban planning on parking demand, which is not addressed here, and, secondly, the choice
of mobility modes, which is discussed here. The choice of mobility modes may, on one hand, require
smart parking management and parking information, which is a result of the tracking technology discussed
before. On the other hand an informed or incentivized choice of mobility modes may even
lead to less parking demand
Reference Systems for Urban Mobility
Full text linkIn the study of urban mobility, understanding the contribution of geospatial data and the relevant
geospatial technologies associated with the collection, storage, and manipulation of geo-referenced
data is essential. Correct understanding of the reference frames used for the collection of geospatial
data ensures that the integrity and accuracy of the data collected is maintained, keeping in mind the
surveying principle, ‘whole to part’. It also ensures that the errors involved in the collection of data
are well within the accuracy range expected for the particular scale of mapping, which may then be
used for computations of distance or area. Geospatial data is collected in a three-dimensional space
and is converted to a two-dimensional space for many practical applications. A large range of map
projections are available for this conversion which, again, maintain different cartographic properties
for any specific application. The Universal Transverse Mercator (UTM) is one such projection, which
has properties that come in handy for our problem of mapping for urban mobility. Global Navigation
Satellite Systems (GNSS) and their integration with cellular network infrastructure have caught
the imagination of people and served as the inspiration for a wide spread of applications such as
automatic vehicle location, tracking systems, navigation, pedestrian navigation systems, intelligent
transportation Systems, and precise positioning of emergency callers, all using a location in some
reference system
Smart parking in fast-growing cities
Full text link"Parking in cities is a challenge everywhere, but to a greater extent for the cities in low- and middle-income countries: Cities that are experiencing rapid urbanization and increasing motorization, where free on-street parking meets haphazard parking behaviour, and where investment capacity for parking infrastructure is limited.
This book is a resource book for those managing the urban parking challenges especially in low- and middle-income countries. This open-access book should immediately help city authorities, engineering firms, and academia world-wide to develop data-driven solutions – solutions of a smart city – for their specific context. This perspective is reflected in the approach of the book. The first part lays out the context of geospatial technologies for urban mobility in smart cities. The second focuses on parking information and management using these technologies, with an emphasis on low and middle-income countries.
The book has grown out of a project funded by the Indian Government, Advanced Parking Information and Management for Indian Traffic, a collaboration between IIT Kanpur and the University of Melbourne.
The Nature of Urban Parking
Full text linkParking is a result of derived and often induced demand, and thus suitable for active management
by tools of data and information services that influence demand and search behavior. But what is the
subject of this management? This is the topic of the current chapter
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